| Flowsheet generation through hierarchical reinforcement learning and graph neural networks L Stops, R Leenhouts, Q Gao, AM Schweidtmann AIChE Journal 69 (1), e17938, 2023 | 36* | 2023 |
| Property prediction of fuel mixtures using pooled graph neural networks RJ Leenhouts, T Larsson, S Verhelst, FH Vermeire Fuel 381, 133218, 2025 | 1 | 2025 |
| Pooling Solvent Mixtures for Solvation Free Energy Predictions RJ Leenhouts, N Morgan, EA Ibrahim, WH Green, FH Vermeire arXiv preprint arXiv:2412.01982, 2024 | | 2024 |
| Graph neural networks for molecular mixture properties R Leenhouts, W Green, F Vermeire AI4bio, Location: Delft, 2024 | | 2024 |
| SolProp: predicting solid solubility of organic solutes for a wide range of conditions using machine learning and thermodynamics R Leenhouts, N Morgan, Y Chung, WH Green, F Vermeire 6th Machine Learning and AI in Bio (Chemical) Engineering Conference, Date …, 2023 | | 2023 |
| Flowsheet Synthesis through Graph-Based Reinforcement Learning RJ Leenhouts, L Stops, SM Shanbhag, Q Gao, AM Schweidtmann 2022 AIChE Annual Meeting, 2022 | | 2022 |
Qinghe GaoDelft university of technology在 tudelft.nl 的电子邮件经过验证
